Palavras-chave
Image classification
Text localization
Scene text detection
Text localization
Scene text detection
Como Citar
CONCEIÇÃO, Jhonatas; TORRES, Ricardo; PINTO, Allan. Library of visual descriptors and machine learning algorithms for texture and text detection. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 27, p. 1–1, 2019. DOI: 10.20396/revpibic2720192800. Disponível em: https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/2800. Acesso em: 18 mar. 2026.
Resumo
In this article, we present the implementation of a solution for the text localization problem. More precisely, the solution presented in this article implements a prototype containing approaches for image characterization based on color and texture visual properties for supporting text region classification. As a result, we present a comparison study of several classifications systems for detecting text regions.
Referências
T. Ojala, M. Pietikainen, and T. Maenpaa, “Multiresolution gray-scale and rotation invariant texture classification with local binary patterns,” IEEE Trans. on Pattern Anal. Mach. Intell., vol. 24, no. 7, pp. 971–987, July 2002.
X. Wang, X. Ding, and C. Liu, “Gabor filters-based feature extraction for character recognition,” Pattern Recogn., vol. 38, no. 3, pp.369–379, Mar. 2005.
R. O. Stehling, M. A. Nascimento, and A. X. Falcão, “A compact and efficient image retrieval approach based on border/interior pixel classification,” in ACM 11th Intl. Conf. on Information and Knowledge Management, 2002, pp. 102–109.
X. Wang, X. Ding, and C. Liu, “Gabor filters-based feature extraction for character recognition,” Pattern Recogn., vol. 38, no. 3, pp.369–379, Mar. 2005.
R. O. Stehling, M. A. Nascimento, and A. X. Falcão, “A compact and efficient image retrieval approach based on border/interior pixel classification,” in ACM 11th Intl. Conf. on Information and Knowledge Management, 2002, pp. 102–109.
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